Pandas DataFrame astype() Method
Example
Return a new DataFrame where the data type of all columns has been set to 'int64':
import pandas as pd
data = {
"Duration": [50, 40, 45],
"Pulse":
[109, 117, 110],
"Calories": [409.1, 479.5, 340.8]
}
df =
pd.DataFrame(data)
newdf = df.astype('int64')
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Definition and Usage
The astype() method returns a new DataFrame
where the data types has been changed to the specified type.
You can cast the entire DataFrame to one specific data type, or you can use a Python Dictionary to specify a data type for each column, like this:
{
'Duration': 'int64',
'Pulse' : 'float',
'Calories': 'int64'
}
Syntax
dataframe.astype(dtype, copy, errors)
Parameters
The copy and errors parameters are keyword arguments.
| Parameter | Value | Description |
|---|---|---|
| dtype | data type, or a dictionary with data types for each column:
{
'Duration': 'int64',
'Pulse' : 'float',
'Calories': 'int64'
} |
Required. Specifies the data type |
| copy | True|False | Optional. Default True. Specifies whether to return a copy (True), or to do the changes in the original DataFrame (False). |
| errors | 'raise'|'ignore' | Optional. Default 'raise'. Specifies whether to ignore errors or raise an exception on error. |
Return Value
a Pandas DataFrame with the changes set according to the specified dtype(s).
